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by Anil-matcha
Unrestricted Open-source alternative to AI video platforms — Free AI image & video generation studio with 500+ models (Flux, Midjourney, Kling, Sora, Veo). No content filters. Self-hosted, MIT licensed.
The free, open-source alternative to AI Video Platforms. Generate AI images and videos using 400+ state-of-the-art models across 14 studios — no content filters, no closed ecosystem, no subscription fees.
Community: Join Discord for discussions and support
▶ Watch: Best AI Image Generator (API) in 2026 (Quality, Price, Uncensored, Editing)
Want to launch this as your own branded AI studio and charge your own customers for it? MuAPI White Label lets you spin up a fully white-labeled version of this app — your logo, your colors, your custom domain, your own pricing — with zero infra to manage. You keep the markup on every generation; MuAPI handles the models, the queue, and the billing plumbing underneath.
studio.yourbrand.com)Plans start at $49/mo. Get started with White Label →
Consumer AI image/video platforms almost all run on paid monthly subscriptions — this is the same playbook you'd run under your own brand:
| Platform | Typical subscription range |
|---|---|
| Midjourney | ~$10–$120/mo (Basic → Mega) |
| Runway | ~$12–$76/mo (Standard → Unlimited), custom Enterprise |
| Kling AI | ~$10–$92/mo across Standard → Premier tiers |
| Luma Dream Machine | ~$10–$100+/mo |
| Pika | ~$8–$58/mo |
(Figures are approximate, general-market ranges and change over time — check each platform's current pricing page before quoting them.) With MuAPI White Label, you set these numbers yourself for your own end users — the subscription revenue is yours.
This is a curated set of high-value hubs, popular distribution tools, and model-specific integrations rather than a directory of every related repository.
Hosted version: https://muapi.ai/open-generative-ai?utm_source=github&utm_medium=readme&utm_campaign=open-generative-ai
Use all studios (Image, Video, Audio, AI Clipping, Vibe Motion, Lip Sync, Cinema, Marketing, Workflows, Agents, Design Agent, Apps, MCP & CLI) directly in your browser — no Node.js, no setup. Sign up for a free account to start generating. The hosted version is always up to date with the latest models.
Follow the creator for updates
One-click installers — no Node.js or terminal required.
| Platform | Download |
|---|---|
| macOS Apple Silicon (M1/M2/M3/M4) | Open Generative AI-1.0.9-arm64.dmg |
| macOS Intel (x64) | Open Generative AI-1.0.9.dmg |
| Windows (x64) | Open Generative AI Setup 1.0.9.exe |
| Linux (Ubuntu x64) | v1.0.9 release (.AppImage / .deb), or build locally with npm run electron:build:linux. |
All releases: github.com/Anil-matcha/Open-Generative-AI/releases
Because the app is not notarized by Apple, macOS Gatekeeper will block it on first launch. Follow these steps:
Step 1 — Mount the DMG and drag the app to /Applications
Step 2 — Open Terminal and run:
xattr -cr "/Applications/Open Generative AI.app"
Step 3 — Right-click the app in /Applications → click Open → click Open again on the dialog
You only need to do this once. After that, the app opens normally.
Alternative (no Terminal):
Windows SmartScreen may show a warning because the installer is not code-signed:
The app will install silently to %LocalAppData% with a Start Menu shortcut.
Linux artifacts are available when building with Electron Builder:
# Build Linux installers (AppImage + .deb)
npm run electron:build:linux
Generated files are written to the release/ folder:
chmod +x "release/Open Generative AI-*.AppImage"
./release/Open\ Generative\ AI-*.AppImage
sudo apt install ./release/open-generative-ai_*_amd64.deb
If AppImage fails to start on older systems, install libfuse2:
sudo apt install libfuse2
Ubuntu 24.04 and later enable a kernel security policy (apparmor_restrict_unprivileged_userns) that blocks Chromium's user-namespace sandbox. If the app fails to start silently or crashes immediately, you have two options:
Option A — Recommended: install the .deb instead.
The .deb package ships an AppArmor profile that grants the required permission automatically on install with no system-wide changes.
Option B — Temporary system fix (AppImage users):
sudo sysctl -w kernel.apparmor_restrict_unprivileged_userns=0
This lasts until next reboot. To make it permanent:
echo 'kernel.apparmor_restrict_unprivileged_userns=0' | sudo tee /etc/sysctl.d/99-userns.conf
Open Generative AI is a free, open-source AI image, video, cinema, and lip sync studio that brings creative workflows to everyone. No content filters, no prompt rejections, no guardrails — just full creative freedom. Powered by Muapi.ai, it supports text-to-image, image-to-image, text-to-video, image-to-video, and audio-driven lip sync generation across models like Flux, Nano Banana, Midjourney, Kling, Sora, Veo, Seedream, Infinite Talk, LTX Lipsync, Wan 2.2, and more — all from a sleek, modern interface you can self-host and customize.
Why Open Generative AI instead of other AI Video Platforms?
For a deep dive into the technical architecture and the philosophy behind the "Infinite Budget" cinema workflow, see our comprehensive guide and roadmap.
The desktop app supports two independent local engines. Pick whichever fits the machine you actually run on:
| Engine | What it is | Best for |
|---|---|---|
| sd.cpp (bundled) | C++ engine from stable-diffusion.cpp, runs on the same machine as the app. Metal GPU on Apple Silicon, CUDA/Vulkan/ROCm on Linux/Windows. | Image-only models. Works on Mac M-series. |
| Wan2GP (BYO server) | HTTP client to a user-run Wan2GP server. The server runs Python + PyTorch on a CUDA/ROCm GPU; the desktop app only sends prompts and receives results. | Video models (Wan 2.2, Hunyuan, LTX) and large image models (Flux, Qwen-Image). NVIDIA/AMD GPU required on the server; the desktop app itself can run on a Mac. |
Both engines share the same UI: open Settings → Local Models to configure each.
| Model | Type | Size | Notes |
|---|---|---|---|
| Z-Image Turbo ⚡ | Diffusion Transformer | 2.5 GB + 2.7 GB aux | 8-step turbo. Heavy on memory. |
| Z-Image Base ⚡ | Diffusion Transformer | 3.5 GB + 2.7 GB aux | 50-step high-quality. Heavy on memory. |
| Dreamshaper 8 | SD 1.5 | 2.1 GB | 20-step versatile. Lightest tested option on Mac. |
| Realistic Vision v5.1 | SD 1.5 | 2.1 GB | 25-step photorealistic |
| Anything v5 | SD 1.5 | 2.1 GB | 20-step anime/illustration |
| SDXL Base 1.0 | SDXL | 6.9 GB | 30-step high-res |
Z-Image models require two shared auxiliary files (downloaded once, shared across both models):
- Qwen3-4B Text Encoder — 2.4 GB
- FLUX VAE — 335 MB
How to use:
All downloads happen inside the app. Nothing is installed system-wide.
By default, sd.cpp stores the engine, model weights, and temporary downloads under Electron's app data directory. Common paths are:
~/Library/Application Support/open-generative-ai/local-ai%APPDATA%\open-generative-ai\local-ai~/.config/open-generative-ai/local-aiTo keep multi-GB model weights on another drive, set OPEN_GENERATIVE_AI_LOCAL_AI_DIR
before launching the desktop app. The app will create bin/, models/, and tmp/
inside that directory, and Settings -> Local Models shows the resolved model folder.
Local engine output and download errors are written to the app process console, so launch
from Terminal or PowerShell when you need troubleshooting logs.
The app does not bundle Python or model weights for Wan2GP. You run Wan2GP yourself on a machine with a CUDA or ROCm GPU and point the desktop app at its URL.
# On your GPU machine
git clone https://github.com/deepbeepmeep/Wan2GP
cd Wan2GP
./install.sh # or install.bat on Windows
python wgp.py --listen --server-name 0.0.0.0 # binds to all interfaces
Then in the desktop app: Settings → Local Models → Wan2GP server, paste the URL (e.g. http://192.168.1.42:7860), click Test, then Save. The Wan2GP models become available — image models in Image Studio, video models reachable via the same generation API (Image Studio rejects video output explicitly; full Video Studio wiring is on the roadmap).
| Model | Type | Notes |
|---|---|---|
| Flux.1 Dev | Image | 1024px, 28 steps |
| Qwen Image | Image | 1024px, 30 steps |
| Wan 2.2 (T2V / I2V) | Video | Slow on consumer GPUs |
| Hunyuan Video | Video | High-quality T2V |
| LTX Video | Video | Fastest video option |
Why a separate server? Wan2GP's runtime (Sage attention, flash-attn, AWQ/GGUF kernels) is CUDA-only — there is no MPS / Apple Silicon path. Treating it as a remote server lets a Mac-only user keep the desktop app while offloading inference to a Linux/Windows GPU box, a gaming PC on the LAN, or a rented RunPod/vast.ai instance.
Local inference is only available in the desktop app. The hosted web version always uses cloud APIs.
If you want to confirm sd.cpp is installed correctly without going through the UI, you can drive sd-cli directly. This is the same binary the app uses.
# 1. App data layout (created on first app launch)
APP_DATA="${OPEN_GENERATIVE_AI_LOCAL_AI_DIR:-$HOME/Library/Application Support/open-generative-ai/local-ai}"
ls "$APP_DATA/bin" # sd-cli, libstable-diffusion.dylib
ls "$APP_DATA/models" # whatever you've downloaded
# 2. Grab a small SD 1.5 model directly (Dreamshaper 8, ~2 GB)
curl -L --fail --progress-bar \
-o "$APP_DATA/models/DreamShaper_8_pruned.safetensors" \
"https://huggingface.co/Lykon/DreamShaper/resolve/main/DreamShaper_8_pruned.safetensors"
# 3. Run a single 512x512 / 12-step inference
DYLD_LIBRARY_PATH="$APP_DATA/bin" "$APP_DATA/bin/sd-cli" \
-m "$APP_DATA/models/DreamShaper_8_pruned.safetensors" \
-p "a serene mountain lake at sunrise, oil painting" \
-o /tmp/sd15-test.png \
--steps 12 -H 512 -W 512 --cfg-scale 7.5 --seed 42 \
--sampling-method euler_a
A healthy run on Apple Silicon prints total params memory size = 1969.78MB (VRAM 1969.78MB, RAM 0.00MB) (Metal-backed) and produces a coherent 512×512 PNG. If VRAM is 0.00MB instead, the dylib is CPU-only — check otool -L "$APP_DATA/bin/libstable-diffusion.dylib" | grep -i metal and reinstall the engine from Settings → Local Models if Metal is missing.
The Image Studio automatically switches between two model sets:
| Mode | Trigger | Models | Prompt |
|---|---|---|---|
| Text-to-Image | Default (no image) | 50+ t2i models (Flux, Nano Banana 2, Seedream 5.0, Ideogram, GPT-4o, Midjourney…) | Required |
| Image-to-Image | Reference image uploaded | 55+ i2i models (Kontext, Nano Banana 2 Edit, Seedream 5.0 Edit, Seededit, Upscaler…) | Optional |
| Model | Type | Key Features |
|---|---|---|
| Nano Banana 2 | Text-to-Image | Google Gemini 3.1 Flash Image · Resolution 1K/2K/4K · Google Search enhancement · aspect ratio auto |
| Nano Banana 2 Edit | Image-to-Image | Up to 14 reference images · Resolution 1K/2K/4K · Google Search enhancement |
| Seedream 5.0 | Text-to-Image | ByteDance · Quality basic/high · 8 aspect ratios · up to 4K |
| Seedream 5.0 Edit | Image-to-Image | ByteDance · Natural language style transfer · Quality basic/high |
| MiniMax Image 01 | Text-to-Image | MiniMax · 8 aspect ratios · up to 4 images per request · 1500 char prompt |
Models that accept multiple reference images expose a multi-select picker when active:
| Model | Max Images |
|---|---|
| Nano Banana 2 Edit | 14 |
| Nano Banana Edit | 10 |
| Flux Kontext Dev I2I | 10 |
| Kling O1 Edit Image | 10 |
| GPT-4o Edit / GPT Image 1.5 Edit | 10 |
| Bytedance Seedream Edit v4 / v4.5 | 10 |
| Vidu Q2 Reference to Image | 7 |
| Flux 2 Flex/Pro Edit | 8 |
| Nano Banana Pro Edit | 8 |
| Flux Kontext Pro/Max I2I | 2 |
| Wan 2.5/2.6 Image Edit | 2–3 |
| Qwen Image Edit Plus / 2511 | 3 |
| GPT-4o Image to Image | 5 |
| Flux 2 Klein 4b/9b Edit | 4 |
When a multi-image model is selected the upload trigger switches to multi-select mode:
+ badge appears when more slots are availableThe Video Studio follows the same pattern:
| Mode | Trigger | Models | Prompt |
|---|---|---|---|
| Text-to-Video | Default (no image) | 40+ t2v models (Kling, Sora, Veo, Wan, Seedance 2.0, Hailuo, Runway…) | Required |
| Image-to-Video | Start frame uploaded | 60+ i2v models (Kling I2V, Veo3 I2V, Runway I2V, Wan I2V, Seedance 2.0 I2V, Midjourney I2V…) | Optional |
| Model | Type | Key Features |
|---|---|---|
| Seedance 2.0 | Text-to-Video | ByteDance · Aspect ratios 16:9 / 9:16 / 4:3 / 3:4 · Duration 5 / 10 / 15s · Quality basic/high |
| Seedance 2.0 I2V | Image-to-Video | ByteDance · Animate images into video · Up to 9 reference images · Aspect ratios 16:9 / 9:16 / 4:3 / 3:4 · Duration 5 / 10 / 15s · Quality basic/high |
| Seedance 2.0 Extend | Video Extension | ByteDance · Seamlessly continue any Seedance 2.0 generation · Preserves style, motion & audio · Optional continuation prompt · Duration 5 / 10 / 15s · Quality basic/high |
| Grok Imagine T2V | Text-to-Video | xAI · Duration 6 / 10 / 15s · Modes: fun / normal / spicy · Aspect ratios 9:16 / 16:9 / 2:3 / 3:2 / 1:1 |
| Grok Imagine I2V | Image-to-Video | xAI · Duration 6 / 10 / 15s · Modes: fun / normal / spicy · Cinematic motion from still images |
| MiniMax Hailuo 02 / 2.3 Standard & Pro | Text-to-Video / Image-to-Video | MiniMax · Full HD video · Multiple aspect ratios · Fast variant included |
The Lip Sync Studio generates audio-driven talking videos using 9 models across two input modes:
| Mode | Trigger | Description |
|---|---|---|
| Portrait Image | Default | Upload a portrait image + audio file → animated talking video |
| Video | Switch to Video mode | Upload an existing video + audio file → lipsync video |
| Model | Endpoint | Resolutions | Prompt |
|---|---|---|---|
| Infinite Talk | infinitetalk-image-to-video | 480p, 720p | Optional |
| Wan 2.2 Speech to Video | wan2.2-speech-to-video | 480p, 720p | Optional |
| LTX 2.3 Lipsync | ltx-2.3-lipsync | 480p, 720p, 1080p | Optional |
| LTX 2 19B Lipsync | ltx-2-19b-lipsync | 480p, 720p, 1080p | Optional |
| Model | Endpoint | Resolutions | Prompt |
|---|---|---|---|
| Sync Lipsync | sync-lipsync | — | — |
| LatentSync | latentsync-video | — | — |
| Creatify Lipsync | creatify-lipsync | — | — |
| Veed Lipsync | veed-lipsync | — | — |
| Infinite Talk V2V | infinitetalk-video-to-video | 480p, 720p | Optional |
How it works:
Generation history is saved separately in lipsync_history and pending jobs resume automatically on page reload.
The Workflow Studio lets you build and run multi-step AI pipelines without writing code.
Key capabilities:
💡 Want to add workflows to your own app? Check out Vibe Workflow — the open-source workflow engine powering this feature. Drop it into any project.
The Cinema Studio offers precise control over the virtual camera, translating your choices into optimized prompt modifiers:
| Category | Available Options |
|---|---|
| Cameras | Modular 8K Digital, Full-Frame Cine Digital, Grand Format 70mm Film, Studio Digital S35, Classic 16mm Film, Premium Large Format Digital |
| Lenses | Creative Tilt, Compact Anamorphic, Extreme Macro, 70s Cinema Prime, Classic Anamorphic, Premium Modern Prime, Warm Cinema Prime, Swirl Bokeh Portrait, Vintage Prime, Halation Diffusion, Clinical Sharp Prime |
| Focal Lengths | 8mm (Ultra-Wide), 14mm, 24mm, 35mm (Human Eye), 50mm (Portrait), 85mm (Tight Portrait) |
| Apertures | f/1.4 (Shallow DoF), f/4 (Balanced), f/11 (Deep Focus) |
Every image you upload is saved locally (URL + thumbnail) so you never upload the same file twice:
localStorage)Most users want the desktop app, not this dev path. If you just want to run Open Generative AI on your machine, download a prebuilt installer instead — no Node.js required. The instructions below are for contributors building from source.
Pick the entry point that matches your goal:
npm run electron:devnpm run dev# Clone the repository (with submodules — required for the workflow + agent packages)
git clone --recurse-submodules https://github.com/Anil-matcha/Open-Generative-AI.git
cd Open-Generative-AI
# If you already cloned without --recurse-submodules, run this once:
# git submodule update --init --recursive
# Install dependencies + build workspace packages (studio, workflow, agents).
# This step is REQUIRED — `npm install` alone is not enough; the workspaces
# need to be built before either dev script will work.
npm run setup
# Then start ONE of:
npm run electron:dev # Desktop app (Electron + Vite) — recommended
npm run dev # Hosted web version (Next.js) → http://localhost:3000
You'll be prompted to enter your Muapi API key on first use (skip the key if you only plan to use local models).
Troubleshooting —
Couldn't find a 'pages' directory: this means Next.js can't see theapp/folder. Confirm you're runningnpm run devfrom the repo root (the directory that containsapp/,package.json, andnext.config.mjs), and that you cloned with submodules. Re-runnpm run setupifpackages/Vibe-Workfloworpackages/agentsare empty.
npm run build
npm run start
Build native desktop apps with Electron:
# macOS (DMG — Intel + Apple Silicon)
npm run electron:build
# Windows (NSIS installer — x64 + ARM64)
npm run electron:build:win
# Linux (AppImage + DEB — x64)
npm run electron:build:linux
# Both platforms in one pass
npm run electron:build:all
Installers are output to the release/ folder. Pre-built binaries are also available on the Releases page.
The app is a Next.js monorepo with a shared packages/studio component library.
Open-Generative-AI/
├── app/ # Next.js App Router
│ ├── layout.js # Root layout (Tailwind, fonts)
│ ├── page.js # Redirects → /studio
│ └── studio/
│ └── page.js # Studio page — renders StandaloneShell
├── components/
│ ├── StandaloneShell.js # Tab nav + BYOK (API key from localStorage)
│ └── ApiKeyModal.js # API key entry modal
├── packages/
│ └── studio/ # Shared React component library
│ └── src/
│ ├── index.js # Exports: ImageStudio, VideoStudio, AudioStudio, ClippingStudio, VibeMotionStudio, LipSyncStudio, RecastStudio, CinemaStudio, MarketingStudio, WorkflowStudio, AgentStudio, DesignAgentStudio, AppsStudio, AiInfluencerStudio, McpCliStudio
│ ├── models.js # 400+ model definitions (single source of truth)
│ ├── muapi.js # API client (named exports, apiKey as first param)
│ └── components/
│ ├── ImageStudio.jsx # Dual-mode t2i/i2i studio
│ ├── VideoStudio.jsx # Dual-mode t2v/i2v studio
│ ├── LipSyncStudio.jsx # Portrait/video + audio → talking video
│ ├── CinemaStudio.jsx # Pro studio with camera controls
│ └── WorkflowStudio.jsx # Multi-step pipeline builder & playground
├── next.config.mjs # transpilePackages: ['studio']
├── tailwind.config.js
└── package.json # workspaces: ["packages/studio"]
The packages/studio library is also consumed by the hosted version on muapi.ai — model updates made in packages/studio/src/models.js apply to both the self-hosted app and the hosted version automatically.
The app communicates with Muapi.ai using a two-step pattern:
POST /api/v1/{model-endpoint} with prompt and parametersGET /api/v1/predictions/{request_id}/result until status is completedAuthentication uses the x-api-key header. During development, a Vite proxy handles CORS by routing /api requests to https://api.muapi.ai.
File uploads use POST /api/v1/upload_file (multipart/form-data) and return a hosted URL that is passed to image-conditioned models. For multi-image models the full images_list array is forwarded to the API in one request.
Lip sync jobs use the same two-step pattern: a dedicated processLipSync() method accepts image_url or video_url alongside audio_url, dispatches to the model's endpoint, and polls until the output video URL is available.
| Category | Count | Examples |
|---|---|---|
| Text-to-Image | 70+ | Flux Dev, Nano Banana 2, Seedream 5.0, Ideogram v3, Midjourney v7, GPT-4o, SDXL |
| Image-to-Image | 70+ | Nano Banana 2 Edit (×14), Flux Kontext Pro, GPT-4o Edit, Seededit v3, Upscaler, Background Remover |
| Text-to-Video | 85+ | Kling v3, Sora 2, Veo 3, Wan 2.6, Seedance 2.0, Seedance 2.0 Extend, Seedance Pro, Hailuo 2.3, Runway Gen-3 |
| Image-to-Video | 120+ | Kling v2.1 I2V, Veo3 I2V, Runway I2V, Seedance 2.0 I2V, Midjourney v7 I2V, Hunyuan I2V, Wan2.2 I2V |
| Video-to-Video | 35+ | Video effects, AI Clipping, Vibe Motion, video-conditioned edits |
| Lip Sync | 15 | Infinite Talk I2V, Wan 2.2 Speech to Video, LTX 2.3 Lipsync, LTX 2 19B Lipsync, Sync, LatentSync, Creatify, Veed, Infinite Talk V2V |
| Body Swap / Recast | 3 | Subject/appearance recast across image and video |
| Audio | 15+ | Text-to-music, remix, and audio editing models |
(Counts verified against packages/studio/src/models.js — total 420+ models across these 8 categories, plus additional models surfaced through Marketing, Agent, and Design Agent studios.)
packages/studio libraryOpen Generative AI is a community-driven, open-source alternative that provides similar creative capabilities without the closed ecosystem:
| Other providers | Open Generative AI | |
|---|---|---|
| Cost | Subscription-based | Free (open-source) |
| Content filters | Yes — prompts blocked or altered | None |
| Restrictions | Platform guardrails enforced | Full creative freedom |
| Models | Proprietary | 400+ open & commercial models |
| Multi-image input | Limited | Up to 14 images per request |
| Lip sync | No | 9 models, image & video modes |
| Hosted version | Subscription | Free at muapi.ai/open-generative-ai |
| Self-hosting | No | Yes |
| Customizable | No | Fully hackable |
| Data privacy | Cloud-based | Your data stays local |
| Source code | Closed | MIT licensed |
MIT
Built with Muapi.ai — the unified API for AI image and video generation models.
Deep Dive: For more details on the "AI Influencer" engine, upcoming "Popcorn" storyboarding features, and the future of this project, read the full technical overview.
Looking for a free, open-source AI Video Platform? Open Generative AI is an open-source AI image and video generation studio — with no content filters that you can self-host, customize, and extend.
Taste-Skill - gives your AI good taste. stops the AI from generating boring, generic slop